Social weather: A review of crowdsourcing-assisted meteorological knowledge services through social cyberspace
文献类型：期刊论文
| 作者 | Zhu, Yifan1; Zhang, Sifan1; Li, Yinan1; Lu, Hao1,4 ; Shi, Kaize1; Niu, Zhendong1,2,3
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| 刊名 | GEOSCIENCE DATA JOURNAL
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| 出版日期 | 2019-12-18 |
| 页码 | 19 |
| 关键词 | crowdsourcing data-driven knowledge services meteorological services social space |
| ISSN号 | 2049-6060 |
| DOI | 10.1002/gdj3.85 |
| 通讯作者 | Niu, Zhendong(zniu@bit.edu.cn) |
| 英文摘要 | Crowdsourcing has significantly motivated the development of meteorological services. Starting from the beginning of 2010s and highly motivating after 2014, crowdsourcing-driven meteorological services have evolved from a single collection and observation of data to the systematic acquisition, analysis and application of these data. In this review, by focusing on papers and databases that have combined crowdsourcing methods to promote or implement meteorological knowledge services, we analysed the relevant literature in three dimensions: data collection, information analysis and meteorological knowledge applications. First, we selected the potential data sources for crowdsourcing and discussed the characteristics of the collected data in four dimensions: consciousness, objectiveness, mobility and multidisciplinary. Second, based on the purpose of these studies and the extent of utilizing data as well as knowledge, we categorize the crowdsourcing-based meteorological analysis into three levels: relationship discovery, knowledge generalization and systemized service. Third, according to the application scenario, we discussed the applications that have already been put into use, and we suggest current challenges and future research directions. These previous studies show that the use of crowdsourcing in social space can expand the coverage as well as enhance the performance of meteorological service. It was also evident that current researches are contributing towards a systemic and intelligent knowledge service to establish a better bridge among academic, industrial and individual community. |
| WOS关键词 | CLIMATE-CHANGE COMMUNICATION ; MEDIA ; TWITTER ; SYSTEM ; MODEL ; ATTENTION ; SCIENCE ; STORM ; DISCUSSIONS ; TEMPERATURE |
| 资助项目 | China's National Strategic Basic Research Program (973 Program)[2012CB720700] ; Public Weather Service Center of China Meteorological Administration ; National Natural Science Foundation of China[61370137] ; Ministry of Education-China Mobile Research Foundation Project[2016/2-7] ; Postgraduate Education Research Project of Beijing Institute of Technology[2017JYYJG-004] |
| WOS研究方向 | Geology ; Meteorology & Atmospheric Sciences |
| 语种 | 英语 |
| WOS记录号 | WOS:000503075300001 |
| 出版者 | WILEY |
| 资助机构 | China's National Strategic Basic Research Program (973 Program) ; Public Weather Service Center of China Meteorological Administration ; National Natural Science Foundation of China ; Ministry of Education-China Mobile Research Foundation Project ; Postgraduate Education Research Project of Beijing Institute of Technology |
| 源URL | [http://ir.ia.ac.cn/handle/173211/29463]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室 |
| 通讯作者 | Niu, Zhendong |
| 作者单位 | 1.Beijing Inst Technol, Sch Comp Sci & Technol, Beijing 100081, Peoples R China 2.Univ Pittsburgh, Sch Comp & Informat, Pittsburgh, PA USA 3.Beijing Inst Technol, Lib, Beijing, Peoples R China 4.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhu, Yifan,Zhang, Sifan,Li, Yinan,et al. Social weather: A review of crowdsourcing-assisted meteorological knowledge services through social cyberspace[J]. GEOSCIENCE DATA JOURNAL,2019:19. |
| APA | Zhu, Yifan,Zhang, Sifan,Li, Yinan,Lu, Hao,Shi, Kaize,&Niu, Zhendong.(2019).Social weather: A review of crowdsourcing-assisted meteorological knowledge services through social cyberspace.GEOSCIENCE DATA JOURNAL,19. |
| MLA | Zhu, Yifan,et al."Social weather: A review of crowdsourcing-assisted meteorological knowledge services through social cyberspace".GEOSCIENCE DATA JOURNAL (2019):19. |
入库方式： OAI收割
来源：自动化研究所
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